Disaggregate energy efficiency of regions in Taiwan

Jin-Li Hu*, Ming Chung Chang, Hui Wen Tsay

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Purpose: The purpose of this paper is to explore Taiwan’s regional energy efficiency trend and complement the work of the total-factor energy efficiency (TFEE) index proposed by Hu and Wang (2006). It further extends panel data stochastic frontier analysis (SFA) modeling for estimating disaggregate energy efficiency. Design/methodology/approach: This paper applies the panel data stochastic production frontier to estimate the TFEE scores for 20 administrative regions in Taiwan over the period 2004-2015. The SFA models include five inputs (employed population, amount of productive electricity power consumed, amount of electricity consumed for household and non-household electric lighting, amount of gasoline sales, and amount of diesel sales) and one output (total real income in the base year of 2011). Findings: This research concludes with three main findings: the inefficient administrative regions of Taiwan include mostly large industrial parks and the petrochemical industry cluster; the top five administrative regions with inefficient diesel use are mostly metropolitan areas that the concern of air pollution caused by diesel system arouses the awareness to use less diesel fuel; and the average TFEE score on household and non-household electric lighting is higher than the usage efficiency of productive electricity power, gasoline, and diesel, but there is still room for efficiency improvement. Originality/value: Most administrative regions in Taiwan are not efficient in almost all kinds of energy use. The results show that the efficiencies of using productive electricity power, gasoline, and diesel need to be improved a lot more.

Original languageEnglish
Pages (from-to)34-48
Number of pages15
JournalManagement of Environmental Quality: An International Journal
Issue number1
StatePublished - 1 Jan 2018


  • Panel data
  • Stochastic frontier analysis (SFA)
  • Total-factor energy efficiency (TFEE)


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